"...in an environment punctuated by slow, progressive changes followed by cataclistic changes in the opposite direction, individuals that track the enviromment better will overfit (and die). More inaccurate individuals will be the ones surviving long term."
Reading this made me think of the numerous financial firms in history that become very efficient at making money in a particular type of market environment, which inevitably changes suddenly in unexpected ways, causing those financial firms to blow up and maybe even start a financial crisis:
'When Genius Failed' is a terrific book about the ironically-named efficiency-focused 'Long Term Capital Management' hedge fund which was bailed out in the 1998 crisis.
I don't think humans evolve to be inaccurate - I think a better description is that they evolve to not all be the same. If you look at two species, the one that is very uniform is more likely to die out over the long term than the one that has more variation. That variation can be physical, or in the mind and how it makes choices. But this variation makes the species more adaptable when conditions change drastically.
If you look at the long term, in the world that the article describes (slow, gradual with rare cataclysmic changes), most wrong decision makers will still die at a higher chance than correct decision makers. It's just in those rare situations that they survive.
That's a stretch, because it implies intent for diversity. Mass extinction through a lack of robustness is definitely something that natural selection selects for, but the inverse is true where too much genetic variability leads to less reproduction, and a drift towards uniformity over generations.
The bigger assumption in this article is in what natural selection selects for with humans. For sole individuals in any species, you typically need only to live long enough to reproduce viable offspring. With humans, we've evolved intelligence that has lead to a tribal culture.
That means that natural selection doesn't apply to the individual, but the majority of the species. The best individual of the entire human species is enough to hold natural selection back for everyone else (i.e. vaccines, engineering feats, etc.). That doesn't mean we've evolved to making bad decisions, it just means that the collective knowledge of our species is now being subjected to natural selection instead.
Evolution does not understand and does not optimize for the survival and flourishing of a species. There are three reasons why members of a species vary - either the variance is the result of a beneficial gene, or it's the result of random changes to irrelevant genes, or the species is partway through fixing a new beneficial mutation through the entire population.
So the more complicated explanation as to why humans vary is that humans have a specific set of adaptations for learning and filling their place in the social environment. This is the entire point of childhood - trying things, seeing what works well, doing more of it, and winding up a person who does the sorts of things that work well for them. This means that if you happen to be gifted with bad eyesight and good verbal processing, you'll get early successes at storytelling that lead you to that sort of role as an adult.
That, in a nutshell, is why humans have such variance. It's the result of childhood, which is a specific algorithm that genes use to find and exploit the things the hosts happen to be better at.
And this built-in ability to vary oneself is helpful both for the strong and the weak, the pretty and the ugly, the clever and the dull, and so forth. It means instead of over-fitting for behaviors that work for the strong, the trait enacts a strategy that does strong-person behavior in strong people and weak-person behavior in weak people.
Related to this topic: someone (Derbasti) once recommended me [1] "Thinking: Fast and Slow" by economy Nobel-winning Kahneman. This is a book about dozens of ways humans fail to reason properly and a huge part of this book addresses the problem of heuristics we use to estimate risk, probability, costs... absolutely a must-read.
You have some system that tried to balance bias, variance, and utility. Sometimes that best way to do that is to have some bias. The classic example of this is you may jump when you see something that looks like a predator, but then turns out not to be. The cost of being wrong (see nothing when predator, see predator when nothing) means it's optimal to sometimes see danger that isn't there.
That's the argument for racial profiling. Not making any argument for or against, just pointing out something interesting. I didn't think about the topic in this context before, as to whether or not it's rational. It's always only been a question of ethics to me. So the natural follow-up question: are various ethics irrational? Again, only a theoretical exercise, not putting my personal views into this.
The argument seems essentially similar to theories on the evolution of aging that suggest we age because senescence improves evolutionary fitness when the environment changes on a comparatively short timescale [1]. The world changes, therefore a race to the bottom arises for ways to improve fitness that also happen to make life miserable and short for individuals. Miserable and short outcompetes hydra-like immortality or naked-mole-rat-like negligible senescence in the vast majority of niches.
I do not think decision making is a good model for this concept. Culture is. In particular:
Traditionalism vs. Progressiveism
as cultural influences: the former acts to not overfit current conditions, while the latter tries to fit current conditions. Both influences have been critical for human survival.
Control theory is a better model for Traditionalism vs Progressivism, in my opinion. Traditionalism works to add damping to the system of cultural expectations, preventing overshoot and oscillation, while Progressivism provides the proportional response necessary to track the cultural ideal.
Crucially, this shows the difference between Traditionalism and just having a lot of cultural context. Culture itself is just weight - more of it is harder to change, but it's the same difficulty no matter how fast you go. Traditionalists, on the other hand, will fight you harder the more quickly you're changing cultural facts.
good observation. makes me think also about the tendency of computers and the internet to actually slow us down in our work!
their general-purpose nature means that our minds take on the additional complexity of context switching as we use our tools for multiple simultaneous tasks, and indeed this generality means that they can be quickly adapted to new contexts. contrast this to specialist tools which, once learned, provide significant increases in efficiency in the specific context to which they have been adapted (including the benefits of increased concentration owing to lack of distraction!) but cannot always be re-engineered easily to suit new contexts.
Interesting argument presented in the paper, though I wouldn't frame it as "we've evolved to be inaccurate": it's really that the world can be so suddenly unpredictable that setting up strong, working paradigms of decision making in the short term can be worse in the long run than just winging it.
It's worth considering, especially in light of the authors' suggestion that we use computer/human decision-making systems to improve performance, as the world is still unpredictable, and can still break our paradigms. The biggest danger of setting up a good system to improve knowledge is that you'll think you've got a perfect one--we could improve our rationality and decision-making with computers for a long time, before an unexpected case cracks the system, and we're left floundering.
maybe a hybrid computer / human solution will fare better
This is the purpose of technology. To enhance our skills. From fire to machine learning, tools are built to make our lives easier and help us make decisions better.
In the end we're better off with more empirical computing in our decision loops. Eventually hopefully we totally replace ourselves with better, more consisitently optimized decision making systems.
While it does make our life easier, machines also brought our down our physical abilities. In modern countries, people are usually not as strong, have less stamina, and their immune system is less potent.
We also see a decrease in the ability to focus with people using a lot devices with screens.
I'm quite concerned of what AI is doing to our brain skills: pattern recognition, memory, data processing and summary... Al that stuff, left untrained, could lead to regression.
We already see a lot of people going to the gym, doing artificial exercice to keep their body in shape. And now we got those popular games to "train your mind" on phones and consoles.
It's a issue IMO, but not an easily solved one. Who don't want to use innovations bringing confort, productivity and increased lifespan ?
technology has no purpose. it is a natural phenomenon that arises without any in-built ethics or direction. technology can manifest as a tool (to amplify human potential) or a machine (to replace human labour). the effect of a technology can be influenced broadly, for example by who owns and promotes a technology (open-source vs proprietary models) and which groups in society it is put to use to benefit.
The takeaways:
- The path to success is through NOT trying to succeed
- To achieve our highest goals we must be willing to abandon them
- It is in you interest that others DO NOT follow the path you think is right
What we perceive as massive gains does not necessarily fit the evolutionary model of massive gains. Many types of spiders can catch a humming bird in their web, but they can't eat it.
Put another way, animals have upper bounds on the positive value they receive from risks. In human terms the first billion is worth vastly more than the second.
Although there's so many factors and chance that influence the results of every decision and you can only have so much information and perspective, so you can only do the best you can.
The map is not the territory. We work with models of how the world works when deciding things, not the actual world, so it's bound to not be 100% accurate.
Computers do the same, although they can crunch a lot more data than we can, they still work with models of the world, not the world itself.
These address the question of whether we are inaccurate. The paper behind the article (http://journals.plos.org/plosone/article?id=10.1371/journal....) addresses the question of why: because evolution favors under-fitting in a world with punctuated equilibria.
For survival reasons the brain needed to evolve to make both quick decisions and well thought decisions.
If a predator appears in front of you you might not be able to give a lot of thinking to the decision of what you need to do.
If you are a nomad during the ice age and you need to collect food and prepare a shelter, or track a prey for long distances, you probably need to give it some thought.
I don't know if we're really that inaccurate, or that the complexity of the problem is vastly underestimated. If we think that making accurate decisions is so simply, we haven't we made AI yet?
[+] [-] cs702|9 years ago|reply
Reading this made me think of the numerous financial firms in history that become very efficient at making money in a particular type of market environment, which inevitably changes suddenly in unexpected ways, causing those financial firms to blow up and maybe even start a financial crisis:
* https://en.wikipedia.org/wiki/List_of_stock_market_crashes_a...
* https://en.wikipedia.org/wiki/List_of_banking_crises
Society might be better off with financial firms that are "dumber!"
[+] [-] pjmorris|9 years ago|reply
[+] [-] robotcookies|9 years ago|reply
If you look at the long term, in the world that the article describes (slow, gradual with rare cataclysmic changes), most wrong decision makers will still die at a higher chance than correct decision makers. It's just in those rare situations that they survive.
[+] [-] bduerst|9 years ago|reply
The bigger assumption in this article is in what natural selection selects for with humans. For sole individuals in any species, you typically need only to live long enough to reproduce viable offspring. With humans, we've evolved intelligence that has lead to a tribal culture.
That means that natural selection doesn't apply to the individual, but the majority of the species. The best individual of the entire human species is enough to hold natural selection back for everyone else (i.e. vaccines, engineering feats, etc.). That doesn't mean we've evolved to making bad decisions, it just means that the collective knowledge of our species is now being subjected to natural selection instead.
[+] [-] ThrustVectoring|9 years ago|reply
So the more complicated explanation as to why humans vary is that humans have a specific set of adaptations for learning and filling their place in the social environment. This is the entire point of childhood - trying things, seeing what works well, doing more of it, and winding up a person who does the sorts of things that work well for them. This means that if you happen to be gifted with bad eyesight and good verbal processing, you'll get early successes at storytelling that lead you to that sort of role as an adult.
That, in a nutshell, is why humans have such variance. It's the result of childhood, which is a specific algorithm that genes use to find and exploit the things the hosts happen to be better at.
And this built-in ability to vary oneself is helpful both for the strong and the weak, the pretty and the ugly, the clever and the dull, and so forth. It means instead of over-fitting for behaviors that work for the strong, the trait enacts a strategy that does strong-person behavior in strong people and weak-person behavior in weak people.
[+] [-] d33|9 years ago|reply
[1]: https://news.ycombinator.com/item?id=11555148
[+] [-] lordnacho|9 years ago|reply
You have some system that tried to balance bias, variance, and utility. Sometimes that best way to do that is to have some bias. The classic example of this is you may jump when you see something that looks like a predator, but then turns out not to be. The cost of being wrong (see nothing when predator, see predator when nothing) means it's optimal to sometimes see danger that isn't there.
[+] [-] PakG1|9 years ago|reply
[+] [-] reasonattlm|9 years ago|reply
[1]: https://arxiv.org/abs/1103.4649
[+] [-] SubiculumCode|9 years ago|reply
[+] [-] ThrustVectoring|9 years ago|reply
Crucially, this shows the difference between Traditionalism and just having a lot of cultural context. Culture itself is just weight - more of it is harder to change, but it's the same difficulty no matter how fast you go. Traditionalists, on the other hand, will fight you harder the more quickly you're changing cultural facts.
[+] [-] rhodri|9 years ago|reply
their general-purpose nature means that our minds take on the additional complexity of context switching as we use our tools for multiple simultaneous tasks, and indeed this generality means that they can be quickly adapted to new contexts. contrast this to specialist tools which, once learned, provide significant increases in efficiency in the specific context to which they have been adapted (including the benefits of increased concentration owing to lack of distraction!) but cannot always be re-engineered easily to suit new contexts.
[+] [-] bbctol|9 years ago|reply
It's worth considering, especially in light of the authors' suggestion that we use computer/human decision-making systems to improve performance, as the world is still unpredictable, and can still break our paradigms. The biggest danger of setting up a good system to improve knowledge is that you'll think you've got a perfect one--we could improve our rationality and decision-making with computers for a long time, before an unexpected case cracks the system, and we're left floundering.
[+] [-] AndrewKemendo|9 years ago|reply
This is the purpose of technology. To enhance our skills. From fire to machine learning, tools are built to make our lives easier and help us make decisions better.
In the end we're better off with more empirical computing in our decision loops. Eventually hopefully we totally replace ourselves with better, more consisitently optimized decision making systems.
[+] [-] sametmax|9 years ago|reply
We also see a decrease in the ability to focus with people using a lot devices with screens.
I'm quite concerned of what AI is doing to our brain skills: pattern recognition, memory, data processing and summary... Al that stuff, left untrained, could lead to regression.
We already see a lot of people going to the gym, doing artificial exercice to keep their body in shape. And now we got those popular games to "train your mind" on phones and consoles.
It's a issue IMO, but not an easily solved one. Who don't want to use innovations bringing confort, productivity and increased lifespan ?
[+] [-] rhodri|9 years ago|reply
[+] [-] thedrake|9 years ago|reply
The takeaways: - The path to success is through NOT trying to succeed - To achieve our highest goals we must be willing to abandon them - It is in you interest that others DO NOT follow the path you think is right
[+] [-] manmal|9 years ago|reply
[+] [-] digi_owl|9 years ago|reply
[+] [-] Retric|9 years ago|reply
Put another way, animals have upper bounds on the positive value they receive from risks. In human terms the first billion is worth vastly more than the second.
[+] [-] cableshaft|9 years ago|reply
Although there's so many factors and chance that influence the results of every decision and you can only have so much information and perspective, so you can only do the best you can.
The map is not the territory. We work with models of how the world works when deciding things, not the actual world, so it's bound to not be 100% accurate.
Computers do the same, although they can crunch a lot more data than we can, they still work with models of the world, not the world itself.
[+] [-] astrobase_go|9 years ago|reply
[0]: https://people.hss.caltech.edu/~camerer/Ec101/JudgementUncer... [1]: http://www.math.mcgill.ca/vetta/CS764.dir/bounded.pdf
[+] [-] tlb|9 years ago|reply
[+] [-] partycoder|9 years ago|reply
For survival reasons the brain needed to evolve to make both quick decisions and well thought decisions.
If a predator appears in front of you you might not be able to give a lot of thinking to the decision of what you need to do.
If you are a nomad during the ice age and you need to collect food and prepare a shelter, or track a prey for long distances, you probably need to give it some thought.
[+] [-] projektir|9 years ago|reply
[+] [-] oli5679|9 years ago|reply
[+] [-] unknown|9 years ago|reply
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[+] [-] amelius|9 years ago|reply
[+] [-] posterboy|9 years ago|reply